Welcome to the Reinforcement Learning course.
Here you will find out about:
- foundations of RL methods: value/policy iteration, q-learning, policy gradient, etc.
--- with math & batteries included
- using deep neural networks for RL tasks
--- also known as "the hype train"
- state of the art RL algorithms
--- and how to apply duct tape to them for practical problems.
- and, of course, teaching your neural network to play games
--- because that's what everyone thinks RL is about. We'll also use it for seq2seq and contextual bandits.
Jump in. It's gonna be fun!

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Model-free methods

This week we'll find out how to apply last week's ideas to the real world problems: ones where you don't have a perfect model of your environment.